Trend Detection in Regional-Mean Temperature Series: Maximum, Minimum, Mean, Diurnal Range, and SST

Abstract Regional climate trends are of interest both for understanding natural climate processes and as tests of anthropogenic climate change signatures. Relative to global trends, however, their detection is hampered by smaller datasets and the influence of regional climate processes such as the Southern Oscillation. Regional trends are often presented by authors without demonstration of statistical significance. In this paper, regional-average annual series of air temperature and sea surface temperature for the New Zealand region are analyzed using a systematic statistical approach that selects the optimum statistical model (with respect to serial correlation, linearity, etc.), explicitly models the interannual variability associated with observable regional climate processes, and tests significance. It is found that the residuals are stationary and are a red noise process [ARMA(1,0)] for all the series examined. The SOI and a meridional circulation anomaly index (both high-pass filtered) are “explanat...

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